Honors College Thesis

 

Investigation Into the Use of a Lead Slowing Down Spectrometer for Neutron Cross Section Analysis Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/honors_college_theses/wp988q82h

Descriptions

Attribute NameValues
Creator
Abstract
  • A lead slowing-down spectrometer (LSDS) was modeled in the hopes of beginning a nuclear data development campaign at Oregon State University. An LSDS can be used for neutron interrogation techniques, such as determining isotopic inventory of a sample of unknown components or determining the cross section of a sample of known components. The purpose of this research was to determine the flux profile of a neutron pulse within the LSDS over time and determine the effectiveness of the LSDS for neutron cross section analysis. In order to do this, Monte Carlo N-Particle simulations were used to model the LSDS along with the shielding, detectors, and the room surrounding the device. A variety of different room configurations, shielding, and samples were placed into the model to determine how the coefficients that describe the operation of the LSDS change. The resulting data was a normal-shaped probability distribution function centered at the most abundant neutron energy that can be used to determine the cross section of a sample with about 30% accuracy, which corresponds to the width of the distribution function. Changes to the system caused the coefficients of the LSDS to change by approximately 12% on average, indicating that the flux spectrum within the device is relatively stable regardless of the environment and sample. The modeled irradiation resulted in cross sections with an error relative to the established data ranging from 66.1% to 2990%.
License
Resource Type
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Non-Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language

Relationships

Parents:

This work has no parents.

In Collection:

Items